Low-Complexity Resource Allocation for Dense Cellular Vehicle-to-Everything (C-V2X) Communications
share
Vehicular communications are the key enabler of traffic reduction and road safety improvement referred to as cellular vehicle-to-everything (C-V2X) communications. Considering the numerous transmitting entities in next generation cellular networks, most existing resource allocation algorithms are impractical or non-effective to ensure reliable C-V2X communications which lead to safe intelligent transportation systems. We study a centralized framework to develop a low-complexity, scalable, and practical resource allocation scheme for dense C-V2X communications. The NP-hard sum-rate maximization resource allocation problem is formulated as a mixed-integer non-linear non-convex optimization problem considering both cellular vehicular links (CVLs) and non-cellular VLs (NCVLs) quality-of-service (QoS) constraints. By assuming that multiple NCVLs can simultaneously reuse a single cellular link (CL), we propose two low-complexity sub-optimal matching-based algorithms in four steps. The first two steps provide a channel gain-based CVL priority and CL assignment followed by an innovative scalable min-max channel-gain-based CVL-NCVL matching. We propose an analytically proven closed-form fast feasibility check theorem as the third step. The objective function is transformed into a difference of convex (DC) form and the power allocation problem is solved optimally using majorization-minimization (MaMi) method and interior point methods as the last step. Numerical results verify that our schemes are scalable and effective for dense C-V2X communications. The low-complexity and practicality of the proposed schemes for dense cellular networks is also shown. Furthermore, it is shown that the proposed schemes outperform other methods up to performance.
READ FULL TEXT
